Edutainment Software for the Pepper Robot

Matulik, M.; Vavrecka, Michal; Vidovičová, Lucie

doi:10.1145/3440084.3441194

Cited by 3 publications

(5 citation statements)

References 10 publications

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“…The first discursive theme refers to the way that texts assume multiple intended audiences and consumers, leading to blurred portraits of agency. Pepper robot made by Softbank is now being used deliberately as both entertainer and teacher: "Pepper's conversational skills and ability to provide an edutainment [role] both in terms of education or cognitive training (quizzes and games) and in terms of increasing the users' confidence" [29]. Again, Hayles writes that "because humans and technical systems in a cognitive assemblage are interconnected, the cognitive decisions of each affect the others, with interactions occurring across the full range of human cognition" [3: 118].…”

Section: Discussionmentioning

confidence: 99%

AI Agents, Humans and Untangling the Marketing of Artificial Intelligence in Learning Environments

Pedersen¹,

Duin²

2022

Proceedings of the Annual Hawaii International Conference on System Sciences

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This exploratory study identifies the tangling of proposed relationships between human and nonhuman agents by providing an analysis on how AI technologies are marketed for learning subjects through a critical discourse analysis of corporate advertisements. We ask: Amid these emerging technologies, how are humans and AI technologies framed as agents with agency? How are learners framed by corporate advertising as part of this blurring? We used a public, open-access cultural analytics database and repository, Fabric of Digital Life ('Fabric', https://fabricofdigitallife.com/), to identify a set of artifacts as a dataset for such analysis. Results indicate that advertising promotes corporate products while also promoting idealized social practices for human-computer interaction and humanrobot interaction in learning contexts. Using AI to automate relationships between students and teachers frames AI systems as authorities in both robot and non-robot platforms, blurring and minimizing student and instructor agency in learning environments.

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Section: Discussionmentioning

confidence: 99%

AI Agents, Humans and Untangling the Marketing of Artificial Intelligence in Learning Environments

Pedersen¹,

Duin²

2022

Proceedings of the Annual Hawaii International Conference on System Sciences

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“…The re-orientation to the body brought to light the process of ageing, both in its material and embodied aspects, through which the human body simultaneously shapes and is shaped by society and culture [9] (pp. [16][17][18][19]. In this article, we build on Gilleard and Higgs' argument [9] by focusing on the corporeality of robotic and human bodies as social actants, with embodiment understood from the Societies 2023, 13, 15 2 of 13 position of performing actions on or by the body in realising the social [10] (pp.…”

Section: Background 21 Corporeality Materiality and The Relationality...mentioning

confidence: 99%

“…The red "eye" colour was conceived as threatening by the older users in our project (cf. our previous report on the technical features and project results in [19]). In terms of "hearing and speaking", [20] conclude that several features need to be improved, such as the intonation of the words vocalized by Pepper, resulting in inappropriate responses by the older adult; differences in question-response time (i.e., the timing between Pepper's questions and the responses of the older adult not timely and not matching, leading to confusion among the older users); and the inability to communicate with multiple older adults.…”

Section: The "Failing" Body Of the Technological "Other"mentioning

confidence: 99%

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Materiality, Corporeality, and Relationality in Older Human–Robot Interaction (OHRI)

Vidovičová¹,

Menšíková²

2023

Societies

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This article presents interdisciplinary research on the social and technological aspects of interactions between older adults and the humanoid robot Pepper (SoftBank Robotics). Our case study is based on the regular meetings that are a part of an experimental intervention taking place at the Active Ageing Centre for older adults in Prague, run by the NGO Life 90. Through the methods of participant observation, unstructured interviews, analyses of video recordings from interventions with Pepper, and subsequent reflections on the “user” experience with the robot, we have unpacked the complexity of materiality and corporeality in older human–robot interactions (OHRI) in the context of age and gender. The project brings new applied knowledge, exploring OHRI using concepts relevant to gerotechnologies, informed by studies of materiality and ageing studies.

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“…Speech is one of the most commonly used interaction-recognition techniques in edutainment-based systems, and is a key technology for smooth educational learning and interaction between the system and the user [ 10 , 11 , 12 , 13 , 14 ]. Speech involves the perception of both auditory and visual information and is the most commonly used human engagement and communication mode.…”

Section: Introductionmentioning

confidence: 99%

Noise-Robust Multimodal Audio-Visual Speech Recognition System for Speech-Based Interaction Applications

Jeon

Kim

2022

Sensors

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Speech is a commonly used interaction-recognition technique in edutainment-based systems and is a key technology for smooth educational learning and user–system interaction. However, its application to real environments is limited owing to the various noise disruptions in real environments. In this study, an audio and visual information-based multimode interaction system is proposed that enables virtual aquarium systems that use speech to interact to be robust to ambient noise. For audio-based speech recognition, a list of words recognized by a speech API is expressed as word vectors using a pretrained model. Meanwhile, vision-based speech recognition uses a composite end-to-end deep neural network. Subsequently, the vectors derived from the API and vision are classified after concatenation. The signal-to-noise ratio of the proposed system was determined based on data from four types of noise environments. Furthermore, it was tested for accuracy and efficiency against existing single-mode strategies for extracting visual features and audio speech recognition. Its average recognition rate was 91.42% when only speech was used, and improved by 6.7% to 98.12% when audio and visual information were combined. This method can be helpful in various real-world settings where speech recognition is regularly utilized, such as cafés, museums, music halls, and kiosks.

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Edutainment Software for the Pepper Robot

Cited by 3 publications

References 10 publications

AI Agents, Humans and Untangling the Marketing of Artificial Intelligence in Learning Environments

AI Agents, Humans and Untangling the Marketing of Artificial Intelligence in Learning Environments

Materiality, Corporeality, and Relationality in Older Human–Robot Interaction (OHRI)

Noise-Robust Multimodal Audio-Visual Speech Recognition System for Speech-Based Interaction Applications

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